Results 201 to 210 of about 33,160 (233)

Recursive stochastic subspace identification for structural parameter estimation

SPIE Proceedings, 2009
Identification of structural parameters under ambient condition is an important research topic for structural health monitoring and damage identification. This problem is especially challenging in practice as these structural parameters could vary with time under severe excitation.
C. C. Chang, Z. Li
openaire   +1 more source

STOCHASTIC SUBSPACE IDENTIFICATION GUARANTEEING STABILITY AND MINIMUM PHASE

IFAC Proceedings Volumes, 2005
Abstract This paper presents a stochastic subspace identification algorithm to compute stable, minimum phase models from a stationary time-series data. The algorithm is based on spectral factorization techniques and a stochastic subspace identification method via a block LQ decomposition (Tanaka and Katayama, 2003 c ).
Hideyuki TANAKA, Tohru KATAYAMA
openaire   +1 more source

Imminent Earthquake Analysis Based on Stochastic Subspace Identification

Advanced Materials Research, 2013
A novel imminent earthquake analysis method is proposed. Firstly, BHZ data are acquired from seismic networks, then, structure parameters of part of the earth are identified based on SSI (stochastic subspace identification); finally, imminent earthquake is analyzed based on the results of system identification.
Ling Li, Guo Bin Jin
openaire   +1 more source

Reference based stochastic subspace identification in civil engineering

Inverse Problems in Engineering, 2000
A specific strategy is required when performing vibration tests on civil engineering structures. The use of artificial excitation sources such as shakers or drop weights is often unpractical and expensive. Ambient excitation on the contrary is freely available (traffic, wind), but it causes other challenges.
B. Peeters, G. De Roeck
openaire   +1 more source

Subspace identification for a stochastic model of plague

International Journal of Biomathematics, 2016
In this paper, a stochastic model of plague is first studied by subspace identification. First, the discrete model of plague is obtained based on the classical model. The corresponding stochastic model is proposed for the existence of stochastic disturbances. Second, for the model, the parameter matrices and noise intensity are obtained.
Yu, Miao, Liu, Jianchang
openaire   +2 more sources

On “Subspace Methods” Identification and Stochastic Model Reduction

IFAC Proceedings Volumes, 1994
Abstract In this paper the problem of stochastic model identification from estimated covariances is considered. In this context, we analyze a class of popular subspace identification procedures in the theoretical framework of rational covariance extension and balanced model reduction, and we demonstrate that they are based on a hidden assumption ...
Anders Lindquist, Giorgio Picci
openaire   +1 more source

An experimental validation of the Stochastic Subspace Identification

PAMM, 2004
AbstractIn this contribution we derive and experimentally validate the Stochastic Subspace Identification. Additionally we compare the results with an updated finite element model. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
A. S. Kompalka, S. Reese
openaire   +1 more source

Subspace-based Identification of Stochastic Systems Using Innovation Model

IFAC Proceedings Volumes, 1997
Abstract In this paper a 4SID algorithm is proposed to identify a class of linear stochastic systems from the noisy input-output data sequence. First, the standard linear stochastic models are replaced equivalently by the innovations representation of Kalman filter equation.
Akira Ohsumi, Satoshi Takashima, Kentaro Kameyama   +2 more
openaire   +1 more source

Stochastic subspace system identification using multivariate time-frequency distributions

SPIE Proceedings, 2017
Structural health monitoring assesses structural integrity by processing the measured responses of structures. One particular group in the structural health monitoring research is to conduct the operational modal analysis and then to extract the dynamic characteristics of structures from vibrational responses.
Chia-Ming Chang, Shieh-Kung Huang
openaire   +1 more source

Stochastic subspace identification of linear systems with observation outliers

Proceedings of the 44th IEEE Conference on Decision and Control, 2006
This paper considers a problem of identifying stochastic linear systems subject to observation outliers, where the observation noise contains large values with a low probability. A stochastic subspace identification method for the problem is developed based on a block LQ decomposition, introducing a weighting matrix to delete outputs which are ...
H. Tanaka, J. ALMutawa, T. Katayama
openaire   +1 more source